Development Of Indoor Localization System For Elderly Care Based On Device-free Passive Method

According to some social research, the proportion of the elders weighs increasingly in total population year after year. However, the burden from career drives people overloaded, a consequence of which is that traditional way to take care of elders in family cannot suit modern society trend. Therefore, how to utilize modern information technology into elderly care becomes an important and meaningful research issue.By combining with relative theories, this dissertation mainly focus on the analysis of target indoor location. We present the design, implement and evaluation of a localization based passive elderly care system.Compared with other elderly care system, the advantage of our system is centralized in easy deployment, privacy protection and human-free maintaining.The main contributions in the dissertation can be summarized as follow:(1)Data acquisition technology based on state switching can effectively split the original data stream of different locations and improve the precision of the data set. In addition, this dissertation proposed a data pre-processing solution based on sliding window to resolve the problem of loss packet in the data acquisition process.This solution could fill with the raw data packet loss and improve real-time utilization.(2)Considering privacy issue and some habits and customs of the elders, we choose radio based on device-free passive(DFP) localization method to extract indoor position information.Nearest Neighbor(NN) based DFP localization method is adopted for its unobtrusiveness and privacy-protection to obtain elder’s indoor position. During off-line phase in DFP method, the mean value method is used to construct passive radio map instead of traditional way to take all values into consideration. As a result, the computation complexity reduced from O(N*M*K) to O(N*K) where N is cell number, M is sample number and K is radio link number.We deploy our system into two different environments with different complexity. Experiments show that the proposed method can estimate elder’s indoor position with a very high accuracy, which is98.5439% for room A and 93.0655% for room B on average.